[1] 3.825066e-06
m = matrix(c(50,1000-50,260-50,10000-1000-260+50),nr=2)
colnames(m) = c("DE","Not DE")
rownames(m) = c("In S","Not in S")
kable(m)| DE | Not DE | |
|---|---|---|
| In S | 50 | 210 |
| Not in S | 950 | 8790 |
[1] 3.825066e-06
March 23, 2023
KEGG pathways can be further subdivided into:
\[ p = 1 - \frac{\sum_{i=0}^{k-1}{M\choose i}{N-M \choose n-i}}{N \choose n} \]
dplyr verbs (mutate(), etc.) for altering figures and results.| ID | Description | GeneRatio | BgRatio | pvalue | p.adjust |
|---|---|---|---|---|---|
| R-HSA-69620 | Cell Cycle Checkpoints | 38/330 | 293/10899 | 0 | 0 |
| R-HSA-69618 | Mitotic Spindle Checkpoint | 22/330 | 113/10899 | 0 | 0 |
| R-HSA-2500257 | Resolution of Sister Chromatid Cohesion | 23/330 | 126/10899 | 0 | 0 |
| R-HSA-141424 | Amplification of signal from the kinetochores | 20/330 | 96/10899 | 0 | 0 |
| R-HSA-141444 | Amplification of signal from unattached kinetochores via a MAD2 inhibitory signal | 20/330 | 96/10899 | 0 | 0 |
| R-HSA-9648025 | EML4 and NUDC in mitotic spindle formation | 20/330 | 117/10899 | 0 | 0 |
Treeplots give you a slightly higher level overview by clustering terms based on similarity.
compareCluster function allows you to perform enrichment analysis on multiple gene lists at once.List of 8
$ X1: chr [1:216] "4597" "7111" "5266" "2175" ...
$ X2: chr [1:805] "23450" "5160" "7126" "26118" ...
$ X3: chr [1:392] "894" "7057" "22906" "3339" ...
$ X4: chr [1:838] "5573" "7453" "5245" "23450" ...
$ X5: chr [1:929] "5982" "7318" "6352" "2101" ...
$ X6: chr [1:585] "5337" "9295" "4035" "811" ...
$ X7: chr [1:582] "2621" "2665" "5690" "3608" ...
$ X8: chr [1:237] "2665" "4735" "1327" "3192" ...